• Journal of Korea Water Resources Association
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• v.33 no.6
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• pp.783-791
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• 2000

A multidimensional representation for precipitation, given In the theory proposed by E. Waymire et al. (1984), is used for simulating rainfall in space and time. The model produces moving storms with realistic meso-scale meteorological features in time and space. The first- and second-order statistics derived from observed JX)int gauge data were used to estimate the model parameters based on the Nelder-Mead algorithm of optimization. Then twelve-year traces of rainfall intensities at fixed gage stations were generated at intervals of 1 hours. First- and second-order statistics are evaluated from the above series, which are used for estimating the parameters of one dimensional model of temporal rainfall at a point. As a result from the comparisons of one dimensional model parameters used observed and generated data from multidimensional model, we found that the multidimensional rainfall model generated visually realistic spatial patterns of rainfall as well as realistic temporal hyetographs of rainfall at a point. point.

• Atmosphere
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• v.25 no.1
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• pp.1-18
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• 2015

The most objective way to overcome the limitation of numerical weather prediction model is to represent the uncertainty of prediction by introducing probabilistic forecast. The uncertainty of the numerical weather prediction system developed due to the parameterization of unresolved scale motions and the energy losses from the sub-scale physical processes. In this study, we focused on the growth of model errors. We performed ensemble forecast to represent model uncertainty. By employing the multi-physics scheme (PHYS) and the stochastic kinetic energy backscatter scheme (SKEBS) in simulating typhoon Rusa (2002), we assessed the performance level of the two schemes. The both schemes produced better results than the control run did in the ensemble mean forecast of the track. The results using PHYS improved by 28% and those based on SKEBS did by 7%. Both of the ensemble mean errors of the both schemes increased rapidly at the forecast time 84 hrs. The both ensemble spreads increased gradually during integration. The results based on SKEBS represented model errors very well during the forecast time of 96 hrs. After the period, it produced an under-dispersive pattern. The simulation based on PHYS overestimated the ensemble mean error during integration and represented the real situation well at the forecast time of 120 hrs. The displacement speed of the typhoon based on PHYS was closest to the best track, especially after landfall. In the sensitivity tests of the model uncertainty of SKEBS, ensemble mean forecast was sensitive to the physics parameterization. By adjusting the forcing parameter of SKEBS, the default experiment improved in the ensemble spread, ensemble mean errors, and moving speed.

• Smart Structures and Systems
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• v.29 no.1
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.66-75
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• 2010

The authors argues that the current road updating system based on traditional aerial photograph or multi-spectral satellite image appears to be non-user friendly due to lack of the frequent cartographic representation for the new construction sites. Google Earth are currently being emerged as one of important places to extract road features since the RGB satellite image with high multi-temporal resolution can be accessed freely over large areas. This paper is primarily intended to evaluate optimal threshold of RGB pixel values to extract road features from Google Earth. An empirical study for five experimental sites was conducted to confirm how a RGB picture provided Google Earth can be used to extact the road feature. The results indicate that optimal threshold of RGB pixel values to extract road features was identified as 126, 125, 127 for manual operation which corresponds to 25%, 30%, 19%. Also, it was found that display scale difference of Google Earth was not very influential in tracking required RGB pixel value. As a result the 61cm resolution of Quickbird RGB data has shown the potential to realistically identified the major type of road feature by large scale spatial precision while the typical algorithm revealed successfully the area-wide optimal threshold of RGB pixel for road appeared in the study area.

• The KIPS Transactions:PartA
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• v.11A no.7 s.91
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• pp.555-562
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• 2004

Both global volume reduction and local shape changes of hippocampus within the brain indicate their abnormal neurological states. Hippocampal shape analysis consists of two main steps. First, construct a hippocampal shape representation model ; second, compute a shape similarity from this representation. This paper proposes a novel method for the analysis of hippocampal shape using integrated Octree-based representation, containing meshes, voxels, and skeletons. First of all, we create multi-level meshes by applying the Marching Cube algorithm to the hippocampal region segmented from MR images. This model is converted to intermediate binary voxel representation. And we extract the 3D skeleton from these voxels using the slice-based skeletonization method. Then, in order to acquire multiresolutional shape representation, we store hierarchically the meshes, voxels, skeletons comprised in nodes of the Octree, and we extract the sample meshes using the ray-tracing based mesh sampling technique. Finally, as a similarity measure between the shapes, we compute $L_2$ Norm and Hausdorff distance for each sam-pled mesh pair by shooting the rays fired from the extracted skeleton. As we use a mouse picking interface for analyzing a local shape inter-actively, we provide an interaction and multiresolution based analysis for the local shape changes. In this paper, our experiment shows that our approach is robust to the rotation and the scale, especially effective to discriminate the changes between local shapes of hippocampus and more-over to increase the speed of analysis without degrading accuracy by using a hierarchical level-of-detail approach.

• Journal of Broadcast Engineering
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• v.17 no.5
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• pp.851-863
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• 2012

Retinex algorithm enhances the contrast of image through visibility improvement. However, the conventional Retinex methods may produces color distortions due to error of hue representation and over-saturation since the methods work in RGB color space. In this paper, we propose a new Retinex algorithm with color correction, which improves contrast by using MSR(Multi-Scale Retinex) working in YCbCr color space and adaptively compensates the color saturation based on the maximum color difference table. Our algorithm maps the color difference signals to the correct gamut to prevent over-saturation phenomenon by considering the correlation between luminance and hue dependent saturation. Simulations results show that the proposed method gives better color improvement compared to the conventional methods.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.68-79
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• 2008

Because local cities are different from large cities, they need to reflect their own characteristics of housing market. Thus in order to obtain useful implications for the establishing sound housing market in Jinju City, this paper investigated the characteristics of spatial distribution and determinant factors that affect apartment price in Jinju City. GIS representation of the apartments showed that most of old and small apartments were built in 'land readjustment project' areas executed in 1970s. On the contrary, new and large scale apartment complexes were built quite recently and distributed in the western and southern parts of the city. Next, in order to examine the factors which affect apartment price, this paper subtracted firstly several variables from the related studies. However in order to avoid multi-colinearity, variables were summarized by means of factor analysis. Then, setting apartment price as a dependant variable, 12 hedonic price models were established with 33 independent variables. As results, building age, floor area, accessibility to university and hospital, accessibility to arterial road, and stair-type building were turned out to be significant. These results will be used in making the supply and allocation plan of urban facilities and housing. Finally as conclusions this paper emphasized the need of periodic analysis of local housing market and establishing detailed housing information systems.

• Magazine of the Korean Society of Agricultural Engineers
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• v.24 no.1
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• pp.44-52
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• 1982

Recently, estuary reserovoirs have been actively constructed in Korea and also in Japan there are a large number of estuary reservoirs constructed. But most of the estuary reservoirs are located at the downstream of a river where geographical condition is best for the construction of an enclosing dam. And an effective utilization of water from the estuary reservoir seems to be difficult even if estuary reservoirs are considered to be the water resources the most available for their watershed. Studies on estuary reservoirs so far have been mainly concentrated on the physical and engineering problems of the dam construction itself. The purpose of the present study is to review the estuary reservoir planning in connection with the water resources development and to study a basis of the planning. First, the levels of water use in Korea and Japan were compared with those of other countries in the world. And then, some representative reservoirs were selected to study the roles of a reservoir and water-using conditions in the watershed. Based on the study, a survey was given on the relation between a dam construction upstream and an estuary reservoir construction downstream of a river. Finally, a comprehensive examination was made of the bases of estuary reservoir planning. (1) The estuary reservoir planning is deeply related to the plan for water use develo- pment in the watershed. After the upstream water resources were fully developed up to the most, water reso- urces development by an estuary reservoir should be started. (2) If an estuary lake has a capacity big enough, it can store flood discharge of the watershed without any loss and become a basic facility that will bring about the maxi- mum use of water from the watershed. (3) Estuary reservoirs store water used in the upstream watershed, so recycling of water use is attained by the reservoir. Water in the estuary lake is difficult to be fresh water in its long run. Therefore, estuary reservoir should be located at a place where polluted water is purified and refused. All the planning should be based on the assumption that water in the estuary lake is not fresh but polluted after a long time. (4) The estuary lake can only supply water to the lower basin directly. But the upstream area is benefited from the estuary lake by exchange of irrigation water sources between the lower and the upper area. So a large-scale exchange plan between new and existing water resources is important. By constructing estuary reservoirs and the exchange of water sources between upper and lower areas, the reasonable maximum use of water from the whole watershed is at- tained. (5) The big problem coming from the water resources development by an enclosing estuary is salt water intrusion into the lake. To maintain the estuary lake salt-free, multi-purpose use of the lake should be avoided. It is necessary to take such fundamental measures as abolition of back flow operation of gate, and the closing of the fish port and the fish ladder. The results mentioned above were found in this study and these results of this study could be used for the adequate planning of estuary reservoirs in connection with the maximum water use of the watershed.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.51-58
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• 2023

In this paper, we propose an organ segmentation technique for the automatic extraction of medical diagnostic indicators from X-ray images. In order to calculate diagnostic indicators of heart disease and spinal disease such as VHS(vertebral heart scale) and Cobb angle, it is necessary to accurately segment the thoracic spine, carina, and heart in a chest X-ray image. A deep neural network model in which the high-resolution representation of the image for each layer and the structure converted into a low-resolution feature map are connected in parallel was adopted. This structure enables the relative position information in the image to be effectively reflected in the segmentation process. It is shown that learning performance can be improved by combining the OCR module, in which pixel information and object information are mutually interacted in a multi-step process, and the channel attention module, which allows each channel of the network to be reflected as different weight values. In addition, a method of augmenting learning data is presented in order to provide robust performance against changes in the position, shape, and size of the subject in the X-ray image. The effectiveness of the proposed theory was evaluated through an experiment using 145 human chest X-ray images and 118 animal X-ray images.